914 resultados para Spatial Variability


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The boundary element method is specially well suited for the analysis of the seismic response of valleys of complicated topography and stratigraphy. In this paper the method’s capabilities are illustrated using as an example an irregularity stratified (test site) sedimentary basin that has been modelled using 2D discretization and the Direct Boundary Element Method (DBEM). Site models displaying different levels of complexity are used in practice. The multi-layered model’s seismic response shows generally good agreement with observed data amplification levels, fundamental frequencies and the high spatial variability. Still important features such as the location of high frequencies peaks are missing. Even 2D simplified models reveal important characteristics of the wave field that 1D modelling does not show up.

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No tillage, minimum tillage and conventional tillage practices are commonly used in maize crops in Alentejo, affecting soil physic conditions and determining seeders performance. Seeders distribution can be evaluated in the longitudinal and vertical planes. Vertical plane is specified by seeding depth (Karayel et al., 2008). If, in one hand seeding depth uniformity is a goal for all crop establishment , in the other hand, seeders furrow openers depth control is never constant depending on soil conditions. Seed depth uniformity affects crop emergence, Liu et al. (2004) showed an higher correlation between crop productivity and emergence uniformity than with longitudinal plants distribution. Neto et al. (2007) evaluating seed depth placement by measuring maize mesocotyl length under no tillage conditions in 38 farms concluded that 20% of coefficient of variation suggests the need of improvement seeders depth control mechanisms. The objective of this study was to evaluate casual relationships and create spatial variability maps between soil mechanic resistance and vertical distribution under three different soil practices to improve seed depth uniformity.

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Seismic evaluation methodology is applied to an existing viaduct in the south of Spain, near Granada, which is a medium seismicity region. The influence of both geology and topography in the spatial variability of ground motion are studied as well as seismic hazard analysis and ground motion characterization. Artificial hazard-consistent ground motion records are synthesised applying seismic hazard analysis and site effects are estimated through a diffraction study. Direct BEM is used to calculate the valley displacement response to vertically propagating SV waves and transfer functions are generated allowing the transformation of free field motion to motion at each support. A closed formulae is used to estimate these transfer function. Finally, the results obtained are compared.

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We examined the consequences of the spatial heterogeneity of atmospheric ammonia (NH3) by measuring and modelling NH3 concentrations and deposition at 25 m grid resolution for a rural landscape containing intensive poultry farming, agricultural grassland, woodland and moorland. The emission pattern gave rise to a high spatial variability of modelled mean annual NH3 concentrations and dry deposition. Largest impacts were predicted for woodland patches located within the agricultural area, while larger moorland areas were at low risk, due to atmospheric dispersion, prevailing wind direction and low NH3 background. These high resolution spatial details are lost in national scale estimates at 1 km resolution due to less detailed emission input maps. The results demonstrate how the spatial arrangement of sources and sinks is critical to defining the NH3 risk to semi-natural ecosystems. These spatial relationships provide the foundation for local spatial planning approaches to reduce environmental impacts of atmospheric NH3.

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El frente de un túnel puede colapsar si la presión aplicada sobre el es inferior a un valor limite denominado presión “critica” o “de colapso”. En este trabajo se desarrolla y presenta un mecanismo de rotura rotacional generado punto a punto para el cálculo de la presión de colapso del frente de túneles excavados en terrenos estratificados o en materiales que siguen un criterio de rotura nolineal. La solución propuesta es una solución de contorno superior en el marco del Análisis Límite y supone una generalización del mecanismo de rotura mas reciente existente en la bibliografía. La presencia de un terreno estratificado o con un criterio de rotura no-lineal implica una variabilidad espacial de las propiedades resistentes. Debido a esto, se generaliza el mecanismo desarrollado por Mollon et al. (2011b) para suelos, de tal forma que se puedan considerar valores locales del ángulo de rozamiento y de la cohesión. Además, la estratificación del terreno permite una rotura parcial del frente, por lo que se implementa esta posibilidad en el mecanismo, siendo la primera solución que emplea un mecanismo de rotura que se ajusta a la estratigrafía del terreno. Por otro lado, la presencia de un material con un criterio de rotura no-lineal exige introducir en el modelo, como variable de estudio, el estado tensional en el frente, el cual se somete al mismo proceso de optimización que las variables geométricas del mecanismo. Se emplea un modelo numérico 3D para validar las predicciones del mecanismo de Análisis Limite, demostrando que proporciona, con un esfuerzo computacional significativamente reducido, buenas predicciones de la presión critica, del tipo de rotura (global o parcial) en terrenos estratificados y de la geometría de fallo. El mecanismo validado se utiliza para realizar diferentes estudios paramétricos sobre la influencia de la estratigrafía en la presión de colapso. Igualmente, se emplea para elaborar cuadros de diseño de la presión de colapso para túneles ejecutados con tuneladora en macizos rocosos de mala calidad y para analizar la influencia en la estabilidad del frente del método constructivo. Asimismo, se lleva a cabo un estudio de fiabilidad de la estabilidad del frente de un túnel excavado en un macizo rocoso altamente fracturado. A partir de el se analiza como afectan las diferentes hipótesis acerca de los tipos de distribución y de las estructuras de correlación a los resultados de fiabilidad. Se investiga también la sensibilidad de los índices de fiabilidad a los cambios en las variables aleatorias, identificando las mas relevantes para el diseño. Por ultimo, se lleva a cabo un estudio experimental mediante un modelo de laboratorio a escala reducida. El modelo representa medio túnel, lo cual permite registrar el movimiento del material mediante una técnica de correlación de imágenes fotográficas. El ensayo se realiza con una arena seca y se controla por deformaciones mediante un pistón que simula el frente. Los resultados obtenidos se comparan con las estimaciones de la solución de Análisis Límite, obteniéndose un ajuste razonable, de acuerdo a la literatura, tanto en la geometría de rotura como en la presión de colapso. A tunnel face may collapse if the applied support pressure is lower than a limit value called the ‘critical’ or ‘collapse’ pressure. In this work, an advanced rotational failure mechanism generated ‘‘point-by-point” is developed to compute the collapse pressure for tunnel faces in layered (or stratified) grounds or in materials that follow a non-linear failure criterion. The proposed solution is an upper bound solution in the framework of limit analysis which extends the most advanced face failure mechanism in the literature. The excavation of the tunnel in a layered ground or in materials with a non-linear failure criterion may lead to a spatial variability of the strength properties. Because of this, the rotational mechanism recently proposed by Mollon et al. (2011b) for Mohr-Coulomb soils is generalized so that it can consider local values of the friction angle and of the cohesion. For layered soils, the mechanism needs to be extended to consider the possibility for partial collapse. The proposed methodology is the first solution with a partial collapse mechanism that can fit to the stratification. Similarly, the use of a nonlinear failure criterion introduces the need to introduce new parameters in the optimization problem to consider the distribution of normal stresses along the failure surface. A 3D numerical model is employed to validate the predictions of the limit analysis mechanism, demonstrating that it provides, with a significantly reduced computational effort, good predictions of critical pressure, of the type of collapse (global or partial) in layered soils, and of its geometry. The mechanism is then employed to conduct parametric studies of the influence of several geometrical and mechanical parameters on face stability of tunnels in layered soils. Similarly, the methodology has been further employed to develop simple design charts that provide the face collapse pressure of tunnels driven by TBM in low quality rock masses and to study the influence of the construction method. Finally, a reliability analysis of the stability of a tunnel face driven in a highly fractured rock mass is performed. The objective is to analyze how different assumptions about distributions types and correlation structures affect the reliability results. In addition, the sensitivity of the reliability index to changes in the random variables is studied, identifying the most relevant variables for engineering design. Finally, an experimental study is carried out using a small-scale laboratory model. The problem is modeled in half, cutting through the tunnel axis vertically, so that displacements of soil particles can be recorded by a digital image correlation technique. The tests were performed with dry sand and displacements are controlled by a piston that supports the soil. The results of the model are compared with the predictions of the Limit Analysis mechanism. A reasonable agreement, according to literature, is obtained between the shapes of the failure surfaces and between the collapse pressures observed in the model tests and computed with the analytical solution.

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La investigación de esta tesis se centra en el estudio de técnicas geoestadísticas y su contribución a una mayor caracterización del binomio factores climáticos-rendimiento de un cultivo agrícola. El inexorable vínculo entre la variabilidad climática y la producción agrícola cobra especial relevancia en estudios sobre el cambio climático o en la modelización de cultivos para dar respuesta a escenarios futuros de producción mundial. Es información especialmente valiosa en sistemas operacionales de monitoreo y predicción de rendimientos de cultivos Los cuales son actualmente uno de los pilares operacionales en los que se sustenta la agricultura y seguridad alimentaria mundial; ya que su objetivo final es el de proporcionar información imparcial y fiable para la regularización de mercados. Es en este contexto, donde se quiso dar un enfoque alternativo a estudios, que con distintos planteamientos, analizan la relación inter-anual clima vs producción. Así, se sustituyó la dimensión tiempo por la espacio, re-orientando el análisis estadístico de correlación interanual entre rendimiento y factores climáticos, por el estudio de la correlación inter-regional entre ambas variables. Se utilizó para ello una técnica estadística relativamente nueva y no muy aplicada en investigaciones similares, llamada regresión ponderada geográficamente (GWR, siglas en inglés de “Geographically weighted regression”). Se obtuvieron superficies continuas de las variables climáticas acumuladas en determinados periodos fenológicos, que fueron seleccionados por ser factores clave en el desarrollo vegetativo de un cultivo. Por ello, la primera parte de la tesis, consistió en un análisis exploratorio sobre comparación de Métodos de Interpolación Espacial (MIE). Partiendo de la hipótesis de que existe la variabilidad espacial de la relación entre factores climáticos y rendimiento, el objetivo principal de esta tesis, fue el de establecer en qué medida los MIE y otros métodos geoestadísticos de regresión local, pueden ayudar por un lado, a alcanzar un mayor entendimiento del binomio clima-rendimiento del trigo blando (Triticum aestivum L.) al incorporar en dicha relación el componente espacial; y por otro, a caracterizar la variación de los principales factores climáticos limitantes en el crecimiento del trigo blando, acumulados éstos en cuatro periodos fenológicos. Para lleva a cabo esto, una gran carga operacional en la investigación de la tesis consistió en homogeneizar y hacer los datos fenológicos, climáticos y estadísticas agrícolas comparables tanto a escala espacial como a escala temporal. Para España y los Bálticos se recolectaron y calcularon datos diarios de precipitación, temperatura máxima y mínima, evapotranspiración y radiación solar en las estaciones meteorológicas disponibles. Se dispuso de una serie temporal que coincidía con los mismos años recolectados en las estadísticas agrícolas, es decir, 14 años contados desde 2000 a 2013 (hasta 2011 en los Bálticos). Se superpuso la malla de información fenológica de cuadrícula 25 km con la ubicación de las estaciones meteorológicas con el fin de conocer los valores fenológicos en cada una de las estaciones disponibles. Hecho esto, para cada año de la serie temporal disponible se calcularon los valores climáticos diarios acumulados en cada uno de los cuatro periodos fenológicos seleccionados P1 (ciclo completo), P2 (emergencia-madurez), P3 (floración) y P4 (floraciónmadurez). Se calculó la superficie interpolada por el conjunto de métodos seleccionados en la comparación: técnicas deterministas convencionales, kriging ordinario y cokriging ordinario ponderado por la altitud. Seleccionados los métodos más eficaces, se calculó a nivel de provincias las variables climatológicas interpoladas. Y se realizaron las regresiones locales GWR para cuantificar, explorar y modelar las relaciones espaciales entre el rendimiento del trigo y las variables climáticas acumuladas en los cuatro periodos fenológicos. Al comparar la eficiencia de los MIE no destaca una técnica por encima del resto como la que proporcione el menor error en su predicción. Ahora bien, considerando los tres indicadores de calidad de los MIE estudiados se han identificado los métodos más efectivos. En el caso de la precipitación, es la técnica geoestadística cokriging la más idónea en la mayoría de los casos. De manera unánime, la interpolación determinista en función radial (spline regularizado) fue la técnica que mejor describía la superficie de precipitación acumulada en los cuatro periodos fenológicos. Los resultados son más heterogéneos para la evapotranspiración y radiación. Los métodos idóneos para estas se reparten entre el Inverse Distance Weighting (IDW), IDW ponderado por la altitud y el Ordinary Kriging (OK). También, se identificó que para la mayoría de los casos en que el error del Ordinary CoKriging (COK) era mayor que el del OK su eficacia es comparable a la del OK en términos de error y el requerimiento computacional de este último es mucho menor. Se pudo confirmar que existe la variabilidad espacial inter-regional entre factores climáticos y el rendimiento del trigo blando tanto en España como en los Bálticos. La herramienta estadística GWR fue capaz de reproducir esta variabilidad con un rendimiento lo suficientemente significativo como para considerarla una herramienta válida en futuros estudios. No obstante, se identificaron ciertas limitaciones en la misma respecto a la información que devuelve el programa a nivel local y que no permite desgranar todo el detalle sobre la ejecución del mismo. Los indicadores y periodos fenológicos que mejor pudieron reproducir la variabilidad espacial del rendimiento en España y Bálticos, arrojaron aún, una mayor credibilidad a los resultados obtenidos y a la eficacia del GWR, ya que estaban en línea con el conocimiento agronómico sobre el cultivo del trigo blando en sistemas agrícolas mediterráneos y norteuropeos. Así, en España, el indicador más robusto fue el balance climático hídrico Climatic Water Balance) acumulado éste, durante el periodo de crecimiento (entre la emergencia y madurez). Aunque se identificó la etapa clave de la floración como el periodo en el que las variables climáticas acumuladas proporcionaban un mayor poder explicativo del modelo GWR. Sin embargo, en los Bálticos, países donde el principal factor limitante en su agricultura es el bajo número de días de crecimiento efectivo, el indicador más efectivo fue la radiación acumulada a lo largo de todo el ciclo de crecimiento (entre la emergencia y madurez). Para el trigo en regadío no existe ninguna combinación que pueda explicar más allá del 30% de la variación del rendimiento en España. Poder demostrar que existe un comportamiento heterogéneo en la relación inter-regional entre el rendimiento y principales variables climáticas, podría contribuir a uno de los mayores desafíos a los que se enfrentan, a día de hoy, los sistemas operacionales de monitoreo y predicción de rendimientos de cultivos, y éste es el de poder reducir la escala espacial de predicción, de un nivel nacional a otro regional. ABSTRACT This thesis explores geostatistical techniques and their contribution to a better characterization of the relationship between climate factors and agricultural crop yields. The crucial link between climate variability and crop production plays a key role in climate change research as well as in crops modelling towards the future global production scenarios. This information is particularly important for monitoring and forecasting operational crop systems. These geostatistical techniques are currently one of the most fundamental operational systems on which global agriculture and food security rely on; with the final aim of providing neutral and reliable information for food market controls, thus avoiding financial speculation of nourishments of primary necessity. Within this context the present thesis aims to provide an alternative approach to the existing body of research examining the relationship between inter-annual climate and production. Therefore, the temporal dimension was replaced for the spatial dimension, re-orienting the statistical analysis of the inter-annual relationship between crops yields and climate factors to an inter-regional correlation between these two variables. Geographically weighted regression, which is a relatively new statistical technique and which has rarely been used in previous research on this topic was used in the current study. Continuous surface values of the climate accumulated variables in specific phenological periods were obtained. These specific periods were selected because they are key factors in the development of vegetative crop. Therefore, the first part of this thesis presents an exploratory analysis regarding the comparability of spatial interpolation methods (SIM) among diverse SIMs and alternative geostatistical methodologies. Given the premise that spatial variability of the relationship between climate factors and crop production exists, the primary aim of this thesis was to examine the extent to which the SIM and other geostatistical methods of local regression (which are integrated tools of the GIS software) are useful in relating crop production and climate variables. The usefulness of these methods was examined in two ways; on one hand the way this information could help to achieve higher production of the white wheat binomial (Triticum aestivum L.) by incorporating the spatial component in the examination of the above-mentioned relationship. On the other hand, the way it helps with the characterization of the key limiting climate factors of soft wheat growth which were analysed in four phenological periods. To achieve this aim, an important operational workload of this thesis consisted in the homogenization and obtention of comparable phenological and climate data, as well as agricultural statistics, which made heavy operational demands. For Spain and the Baltic countries, data on precipitation, maximum and minimum temperature, evapotranspiration and solar radiation from the available meteorological stations were gathered and calculated. A temporal serial approach was taken. These temporal series aligned with the years that agriculture statistics had previously gathered, these being 14 years from 2000 to 2013 (until 2011 for the Baltic countries). This temporal series was mapped with a phenological 25 km grid that had the location of the meteorological stations with the objective of obtaining the phenological values in each of the available stations. Following this procedure, the daily accumulated climate values for each of the four selected phenological periods were calculated; namely P1 (complete cycle), P2 (emergency-maturity), P3 (flowering) and P4 (flowering- maturity). The interpolated surface was then calculated using the set of selected methodologies for the comparison: deterministic conventional techniques, ordinary kriging and ordinary cokriging weighted by height. Once the most effective methods had been selected, the level of the interpolated climate variables was calculated. Local GWR regressions were calculated to quantify, examine and model the spatial relationships between soft wheat production and the accumulated variables in each of the four selected phenological periods. Results from the comparison among the SIMs revealed that no particular technique seems more favourable in terms of accuracy of prediction. However, when the three quality indicators of the compared SIMs are considered, some methodologies appeared to be more efficient than others. Regarding precipitation results, cokriging was the most accurate geostatistical technique for the majority of the cases. Deterministic interpolation in its radial function (controlled spline) was the most accurate technique for describing the accumulated precipitation surface in all phenological periods. However, results are more heterogeneous for the evapotranspiration and radiation methodologies. The most appropriate technique for these forecasts are the Inverse Distance Weighting (IDW), weighted IDW by height and the Ordinary Kriging (OK). Furthermore, it was found that for the majority of the cases where the Ordinary CoKriging (COK) error was larger than that of the OK, its efficacy was comparable to that of the OK in terms of error while the computational demands of the latter was much lower. The existing spatial inter-regional variability between climate factors and soft wheat production was confirmed for both Spain and the Baltic countries. The GWR statistic tool reproduced this variability with an outcome significative enough as to be considered a valid tool for future studies. Nevertheless, this tool also had some limitations with regards to the information delivered by the programme because it did not allow for a detailed break-down of its procedure. The indicators and phenological periods that best reproduced the spatial variability of yields in Spain and the Baltic countries made the results and the efficiency of the GWR statistical tool even more reliable, despite the fact that these were already aligned with the agricultural knowledge about soft wheat crop under mediterranean and northeuropean agricultural systems. Thus, for Spain, the most robust indicator was the Climatic Water Balance outcome accumulated throughout the growing period (between emergency and maturity). Although the flowering period was the phase that best explained the accumulated climate variables in the GWR model. For the Baltic countries where the main limiting agricultural factor is the number of days of effective growth, the most effective indicator was the accumulated radiation throughout the entire growing cycle (between emergency and maturity). For the irrigated soft wheat there was no combination capable of explaining above the 30% of variation of the production in Spain. The fact that the pattern of the inter-regional relationship between the crop production and key climate variables is heterogeneous within a country could contribute to one is one of the greatest challenges that the monitoring and forecasting operational systems for crop production face nowadays. The present findings suggest that the solution may lay in downscaling the spatial target scale from a national to a regional level.

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A new methodology is proposed to produce subsidence activity maps based on the geostatistical analysis of persistent scatterer interferometry (PSI) data. PSI displacement measurements are interpolated based on conditional Sequential Gaussian Simulation (SGS) to calculate multiple equiprobable realizations of subsidence. The result from this process is a series of interpolated subsidence values, with an estimation of the spatial variability and a confidence level on the interpolation. These maps complement the PSI displacement map, improving the identification of wide subsiding areas at a regional scale. At a local scale, they can be used to identify buildings susceptible to suffer subsidence related damages. In order to do so, it is necessary to calculate the maximum differential settlement and the maximum angular distortion for each building of the study area. Based on PSI-derived parameters those buildings in which the serviceability limit state has been exceeded, and where in situ forensic analysis should be made, can be automatically identified. This methodology has been tested in the city of Orihuela (SE Spain) for the study of historical buildings damaged during the last two decades by subsidence due to aquifer overexploitation. The qualitative evaluation of the results from the methodology carried out in buildings where damages have been reported shows a success rate of 100%.

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Global air surface temperatures and precipitation have increased over the last several decades resulting in a trend of greening across the Circumpolar Arctic. The spatial variability of warming and the inherent effects on plant communities has not proven to be uniform or homogeneous on global or local scales. We can apply remote sensing vegetation indices such as the Normalized Difference Vegetation Index (NDVI) to map and monitor vegetation change (e.g., phenology, greening, percent cover, and biomass) over time. It is important to document how Arctic vegetation is changing, as it will have large implications related to global carbon and surface energy budgets. The research reported here examined vegetation greening across different spatial and temporal scales at two disparate Arctic sites: Apex River Watershed (ARW), Baffin Island, and Cape Bounty Arctic Watershed Observatory (CBAWO), Melville Island, NU. To characterize the vegetation in the ARW, high spatial resolution WorldView-2 data were processed to create a supervised land-cover classification and model percent vegetation cover (PVC) (a similar process had been completed in a previous study for the CBAWO). Meanwhile, NDVI data spanning the past 30 years were derived from intermediate resolution Landsat data at the two Arctic sites. The land-cover classifications at both sites were used to examine the Landsat NDVI time series by vegetation class. Climate variables (i.e., temperature, precipitation and growing season length (GSL) were examined to explore the potential relationships of NDVI to climate warming. PVC was successfully modeled using high resolution data in the ARW. PVC and plant communities appear to reside along a moisture and altitudinal gradient. The NDVI time series demonstrated an overall significant increase in greening at the CBAWO (High Arctic site), specifically in the dry and mesic vegetation type. However, similar overall greening was not observed for the ARW (Low Arctic site). The overall increase in NDVI at the CBAWO was attributed to a significant increase in July temperatures, precipitation and GSL.

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This dataset contains continuous time series of land surface temperature (LST) at spatial resolution of 300m around the 12 experimental sites of the PAGE21 project (grant agreement number 282700, funded by the EC seventh Framework Program theme FP7-ENV-2011). This dataset was produced from hourly LST time series at 25km scale, retrieved from SSM/I data (André et al., 2015, doi:10.1016/j.rse.2015.01.028) and downscaled to 300m using a dynamic model and a particle smoothing approach. This methodology is based on two main assumptions. First, LST spatial variability is mostly explained by land cover and soil hydric state. Second, LST is unique for a land cover class within the low resolution pixel. Given these hypotheses, this variable can be estimated using a land cover map and a physically based land surface model constrained with observations using a data assimilation process. This methodology described in Mechri et al. (2014, doi:10.1002/2013JD020354) was applied to the ORCHIDEE land surface model (Krinner et al., 2005, doi:10.1029/2003GB002199) to estimate prior values of each land cover class provided by the ESA CCI-Land Cover product (Bontemps et al., 2013) at 300m resolution . The assimilation process (particle smoother) consists in simulating ensemble of LST time series for each land cover class and for a large number of parameter sets. For each parameter set, the resulting temperatures are aggregated considering the grid fraction of each land cover and compared to the coarse observations. Miniminizing the distance between the aggregated model solutions and the observations allow us to select the simulated LST and the corresponding parameter sets which fit the observations most closely. The retained parameter sets are then duplicated and randomly perturbed before simulating the next time window. At the end, the most likely LST of each land cover class are estimated and used to reconstruct LST maps at 300m resolution using ESA CCI-Land Cover. The resulting temperature maps on which ice pixels were masked, are provided at daily time step during the nine-year analysis period (2000-2009).

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Paleo-sea-ice history in the Arctic Ocean was reconstructed using the sea-ice dwelling ostracode Acetabulastoma arcticum from late Quaternary sediments from the Mendeleyev, Lomonosov, and Gakkel Ridges, the Morris Jesup Rise and the Yermak Plateau. Results suggest intermittently high levels of perennial sea ice in the central Arctic Ocean during Marine Isotope Stage (MIS) 3 (25-45 ka), minimal sea ice during the last deglacial (16-11 ka) and early Holocene thermal maximum (11-5 ka) and increasing sea ice during the mid-to-late Holocene (5-0 ka). Sediment core records from the Iceland and Rockall Plateaus show that perennial sea ice existed in these regions only during glacial intervals MIS 2, 4, and 6. These results show that sea ice exhibits complex temporal and spatial variability during different climatic regimes and that the development of modern perennial sea ice may be a relatively recent phenomenon.

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Through the processes of the biological pump, carbon is exported to the deep ocean in the form of dissolved and particulate organic matter. There are several ways by which downward export fluxes can be estimated. The great attraction of the 234Th technique is that its fundamental operation allows a downward flux rate to be determined from a single water column profile of thorium coupled to an estimate of POC/234Th ratio in sinking matter. We present a database of 723 estimates of organic carbon export from the surface ocean derived from the 234Th technique. Data were collected from tables in papers published between 1985 and 2013 only. We also present sampling dates, publication dates and sampling areas. Most of the open ocean Longhurst provinces are represented by several measurements. However, the Western Pacific, the Atlantic Arctic, South Pacific and the South Indian Ocean are not well represented. There is a variety of integration depths ranging from surface to 220m. Globally the fluxes ranged from -22 to 125 mmol of C/m**2/d. We believe that this database is important for providing new global estimate of the magnitude of the biological carbon pump.

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Distributional patterns of glaciological parameters at the Colle Gnifetti core drilling site are described and their interrelationships are brietly discussed. Observations within a stake network established in 1980 furnish information about snow accumulation (short term balance), submergence velocity of ice tlow (long term balance), ram hardness (melt layer stratigraphy), and firn temperature. In addition, a numerical model was used to estimate local variations of available radiant energy. Melt layer formation is considerably more intensive on the south facing parts of the firn saddie where incoming radiation is high. These melt layers seem to effectively protect some of the fallen snow from wind erosion. As a result, balance ist up to one order of magnitude larger on south facing slopes. Heat applied to the surface is therefore positively correlated with balance, whereas the relation between solar radiation and firn temperature is less dear. Distributional patterns of submergence velocity confirm that the observed spatial variability of surface balance is representative for longer time periods and greatly intluences the time scale and the stratigraphy of firn and ice cores from Colle Gnifetti.